Control of a batch polymerization system using hybrid neural network first principle model

• Main Authors: Wei, N.C., Hussain, Mohd Azlan, Wahab, Ahmad Khairi Abdul
• Format: Article
• Published: Canadian Journal of Chemical Engineering 2007
• Subjects: TA Engineering (General). Civil engineering (General); TP Chemical technology
• Online Access: http://eprints.um.edu.my/7046/; http://www.scopus.com/inward/record.url?eid=2-s2.0-38349092708&partnerID=40&md5=ab1ad1231ec2198fdd0453ec74d4760e

In this work, the utilization of neural network in hybrid with first principle models for modelling and control of a batch polymerization process was investigated. Following the steps of the methodology, hybrid neural network (HNN) forward models and HNN inverse model of the process were first developed and then the performance of the model in direct inverse control strategy and internal model control (IMC) strategy was investigated. For comparison purposes, the performance of conventional neural network and PID controller in control was compared with the proposed HNN. The results show that HNN is able to control perfectly for both set points tracking and disturbance rejection studies.